Sudden cardiac arrest (SCA) is a major public health concern, particularly among African Americans where risk of cardiac arrest is higher than that of the general population, and survival is poor. While environmental factors clearly contribute to SCA risk, familial aggregation studies and advances in the molecular genetics of inherited arrhythmias suggest that genetic factors confer susceptibility to SCA in the general population. Identifying these genetic factors will provide insight into the mechanisms of SCA and potentially help target the development of novel drug therapies. Few studies to date have examined genetic risk factors among those of African descent. We propose to systematically investigate the genetic basis of SCA risk among those of African descent, focusing on both rare and common genetic variation in candidate loci selected from biologically important molecular pathways involved in rhythmogenesis, using a targeted sequencing approach. Specifically, we will sequence approximately 100 loci among 1500 African American cases and matched controls, selected from the following sets of candidate genes: genes associated with (1) SCA among those of European descent; (2) intermediate determinants of SCA, such as cardiac conduction and repolarization as measured by the surface EKG (QRS and QT intervals); and (3) Mendelian arrhythmic syndromes that lead to SCA. Beyond establishing statistical associations, we will functionally dissect the role of the genes and variants associated with SCA. We will determine the spatial and temporal distribution of the identified transcripts across a range of developmental and post-natal stages in mice through both whole mount RNA in situ analyses and sectioning of embryonic and postnatal heart. We will use zebrafish to test the hypothesis that titration of selected gene candidates during development will compromise the genesis or function of cardiovascular components. For the identified coding variation, we will compare the capacities of human RNAs containing identified coding variation with their non-variant counterparts to rescue MO-induced effects, and will similarly assay the effects of over-expression. This application represents a multi-center collaborative effort to efficiently link advances in genomics, statistical genetics, and bioinformatics, with new and existing biologic and clinical material to identify genetic determinants of SCD among African Americans. Importantly, we will use model organisms to translate genetic associations into functional studies, to elucidate the roles played by these genes in cardiac electrophysiology and arrhythmias.